Project Summary/Abstract Behaivior is developing a patent-pending platform to predict and prevent addiction relapses and overdoses by treating those in recovery with timely interventions using wearables (like an advanced FitBit) and artificial intelligence. Knowing in real time when someone with opioid use disorder is at a high risk of relapsing revolutionizes the ability to intervene at the right moment to help people stay sober. Our research will contribute to fundamental knowledge about the specific information needed to be gathered in order to accurately detect when someone struggling with opioid use disorder is in a high risk opioid craving/obsession state and enabled the creation of a predictive model for just in time intervention. The number of deaths from opioid overdose is increasing every day, so reducing opioid addiction relapses will save lives and families and it will reduce rearrests, reincarcerations, and rehospitalizations. Over 23 million Americans are addicted to drugs and alcohol, and these addictions cost the U.S. $442 billion per year, according to the US Surgeon General?s office. The majority of treatment tools used to keep those in recovery sober have low or mixed success rates. Many people in recovery end up relapsing multiple times, with the heroin relapse rate around 90%. With the technology that we are developing, Behaivior will detect if someone in recovery is in a red alert craving or ?obsession? state and then, using artificial intelligence, we will provide support in real time by connecting someone to a support network member and/or provide a customized digital intervention. The broader impact/commercial potential of this I-Corps project revolves around the human brain?s proclivity towards substances detrimental to human health and wellbeing, such as dangerous amounts of sugar, salt, and drugs, which is causing global health and safety risks. Inability to avoid these temptations shortens lifespans, increases healthcare costs, and strains resources. This team uses machine learning and pattern recognition AI to identify and react to factors that result in destructive human behaviors. While the initial focus is opioids, this unsupervised learning AI could, in subsequent iterations, be used to identify and react to any behavior -- such as unsafe driving, binge eating, or anger management. Helping people identify the precursors to their behaviors could serve as a type of biofeedback that gives them and their support networks timely and individualized insights, preventions, and interventions, resulting in cost and health benefits across many populations.